Providing broader insights into the pathophysiology of complex diseases through integrative analyses of human -omics datasets, the Hoeschele group collaborates on several projects based on the Multi-Ethnic Study of Atherosclerosis (MESA) with Wake Forest University Medical School. Ongoing methodology research, always motivated by and originating from current collaborations, focuses on combining penalized regression for association studies and gene network inference with control of the False Discovery Rate, causal inference using Network Mendelian Randomization, and biological network inference. Additionally, Dr. Hoeschele has experience and an interest in farm and companion animal genetics and genomics and has worked on genome-wide association studies and genomic predictions.
Working to improve the low-order correlation method.
Providing valuable information in the study of diseases, complex traits, population histories, and evolutionary genetics.
Using SysGenSIM to compare different methods for gene network reconstruction with systems genetic data.
Understanding DNA methylation in the human genome.
Comparing penalized regression with FDR control to single marker analysis for genome-wide association studies.
Researching how cholesterol metabolism underlies obesity leading to type 2 diabetes and cardiovascular disease.